Tools are provided for the manipulation, statistical analysis, and
visualization of taxonomic profiling data. In addition to targeted
case-control studies, the package facilitates scalable exploration of
large population cohorts (Lahti et al. 2014). Whereas sample collections
are rapidly accumulating for the human body and other environments,
few general-purpose tools for targeted microbiome analysis are
available in R. This package supports the independent
phyloseq data format and expands
the available toolkit in order to facilitate the standardization of
the analyses and the development of best practices. See also the
related PathoStat
pipelinemare pipeline,
phylofactor, and structSSI for additional 16S rRNA amplicon
analysis tools in R. The aim is to complement the other available
packages, but in some cases alternative solutions have been necessary
in order to streamline the tools and to improve complementarity.

We welcome feedback, bug reports, and suggestions for new features
from the user community via the issue
tracker and pull
requests. See
the Github site for source
code and other details. These R tools have been utilized in recent
publications and in introductory courses (Salonen et al. 2014, Faust et al. (2015),
Shetty et al. (2017)), and they are released under the Two-clause FreeBSD
license.

4 Ecosystem indices

4.1 Alpha diversity, richness, evenness, dominance, and rarity

Commonly used ecosystem state variables include various indices to quantify
alpha diversities, richness, evenness, dominance, and rarity (see
functions with similar names). We provide a
comprehensive set of such indices via a standardized interface.

The function global calls these indicators with default parameters.
For further options, see
tutorial.

g <- global(atlas1006, index = "gini")

Visually-Weighted Regression curve with smoothed error bars is based on the
can be used to visualize sample variables
(1),
here the relation between age and diversity.
This function operates on standard data frames.